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Adaptive Story Game

Year: 2016
Tags: Deep Learning

 

Traditional story based gameplay is built on pre-made scenarios which are exploited by restricting the number of choices a player can make. Therefore, masking the nature of adoptable gameplay. We digitized all the inputs and outputs of a choice based game in order to train a neural network of how the next challenges must be aligned for the player. The aim is to produce an unpredictable gameplay that is more close to the intelligence level and preferences of the player. The neural network built in this case used an evolutionary approach to build scenarios.
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